MATLAB Implementation of Gaussian Filter with Source Code

The Gaussian filter is a widely used image processing technique that reduces noise through smoothing operations. This implementation provides complete source code for applying Gaussian filtering to images. The function accepts five key parameters: B (input signal/image), irfn (filter characteristics), ipoint (interpolation points), sr (sampling rate), and ncc (normalization control coefficient). Key implementation details include: - The algorithm employs Gaussian convolution kernel generation based on standard deviation parameters - Supports customizable kernel size and sigma values through parameter adjustments - Includes boundary handling mechanisms for edge pixels during convolution - Features optional frequency domain implementation via irfn parameter Users can fine-tune filter performance by modifying parameter values according to specific image processing requirements. Optimal results can be achieved by balancing smoothing strength (controlled through sr and ncc) with detail preservation (managed via ipoint settings). The function returns the filtered output xh, maintaining original image dimensions while effectively reducing high-frequency noise components.